Well testing is the term generally used to describe the process used to obtain valuable well information, e.g., determining a well's production rates, for managing wells and fields. Well tests may be conducted on a regular basis (e.g., daily) or on an as-needed basis for planning future operations. The quality of well tests may vary significantly. Low quality and invalid well tests generate misleading information, thus, must be identified. Well test validation is commonly used to determine the quality of a particular well test.
Traditionally, field operators perform well test validation in the field using limited information. For example, field operators may compare current well test rates with previous well test rates to try to determine whether the current well test is valid. Because these field analyses utilize limited information and rely on small sample sizes and operator capabilities, such field analyses may be subject to unacceptable error rates. Alternatively, engineers remote from the field may analyze the well test data to identify patterns associated with valid and invalid well tests and determine whether a test is valid. This time consuming process relies on the expert knowledge of very experienced engineers for reliable outcomes. Such an approach is not feasible to scale up once the number of well test is large. Moreover, current approaches only provide indication that the well tests are valid and/or invalid and do not provide a fuller explanation of underlying causation for invalid well tests.
Consequently, a need exists for a reliable way to determine the quality of particular well tests. Further, a need exists for a technique to perform well test validation in a rapid manner. Also, a need exists for a scalable practice of well test validation capable of rapidly evaluating even large numbers of well tests. Additionally, a need exists for an approach that identifies the underlying causation for invalid well tests.